Post-deal stack chaos, in plain language
Every broadband acquisition inherits the same mess in a different configuration. Here's what it looks like from the inside — and what each one costs if you let it sit.
1. Dual-run billing without a net
Two billing systems, two sets of rate codes, two dunning processes — and no reconciliation between them. Invoices go missing, payments get misapplied, and nobody can say with confidence what was actually billed last month.
What it costs: revenue leakage, usually discovered quarters later, plus a finance team doing forensics instead of closing the books.
2. Provisioning and billing fall out of sync
The acquired company's provisioning flow doesn't speak to your billing, or vice versa. Services go live but never get billed. Or worse: subscribers get billed for services that were never provisioned, and support eats the fallout.
What it costs: unbilled revenue on one side, churn-driving billing complaints on the other.
3. The field doesn't match the office
Dispatch lives in one tool, the CRM in another, plant records in a third — and the acquired company's techs never fully moved into any of them. Work orders complete, but the completion never becomes a billable event. Trucks roll; the invoice doesn't.
What it costs: unbilled truck rolls, repeat visits, and a field org running on tribal knowledge.
4. Nobody agrees on the system of record
Every vendor in the building swears their system should survive the consolidation — and they're all happy to run a "free assessment" to prove it. Meanwhile the subscriber record diverges a little more every week across three systems.
What it costs: decisions by loudest vendor, data that can't be trusted, and a migration plan nobody believes in.
5. Data you can't migrate because you can't trust it
Subscriber identities, service addresses, equipment records, rate codes, open balances, contract terms — each lives somewhere slightly different, and none of it has been validated since the deal closed. Migrating dirty data just moves the chaos faster.
What it costs: failed cutovers, rollback events, and support queues full of "that's not my bill."
6. The AI pilot that goes nowhere
Somebody green-lit an AI pilot — churn prediction, support copilot, dispatch optimization. It stalls in week three because the CRM doesn't match billing doesn't match plant. The problem was never the model. It was the joins.
What it costs: six figures of pilot spend proving what the data team already knew.
Sound familiar?
These problems are solvable, but not all at once and not in the wrong order. Our 30/60/90 approach starts with stabilization — because you can't consolidate systems that are actively on fire.